Non-contact thermography-based respiratory rate monitoring in a post-anesthetic care unit

Abstract

In patients at high risk of respiratory complications, pulse oximetry may not adequately detect hypoventilation events. Previous studies have proposed using thermography, which relies on infrared imaging, to measure respiratory rate (RR). These systems lack support from real-world feasibility testing for widespread acceptance. This study enrolled 101 spontaneously ventilating patients in a post-anesthesia recovery unit. Patients were placed in a 45° reclined position while undergoing pulse oximetry and bioimpedance-based RR monitoring. A thermography camera was placed approximately 1 m from the patient and pointed at the patient’s face, recording continuously at 30 frames per second for 2 min. Simultaneously, RR was manually recorded. Offline imaging analysis identified the nares as a region of interest and then quantified nasal temperature changes frame by frame to estimate RR. The manually calculated RR was compared with both bioimpedance and thermographic estimates. The Pearson correlation coefficient between direct measurement and bioimpedance was 0.69 (R 2 = 0.48), and that between direct measurement and thermography was 0.95 (R 2 = 0.90). Limits of agreement analysis revealed a bias of 1.3 and limits of agreement of 10.8 (95% confidence interval 9.07 to 12.5) and − 8.13 (− 6.41 to − 9.84) between direct measurements and bioimpedance, and a bias of −0.139 and limits of agreement of 2.65 (2.14 to 3.15) and − 2.92 (− 2.41 to 3.42) between direct measurements and thermography. Thermography allowed tracking of the manually measured RR in the post-anesthesia recovery unit without requiring patient contact. Additional work is required for image acquisition automation and nostril identification. Electronic supplementary material The online version of this article (10.1007/s10877-020-00595-8) contains supplementary material, which is available to authorized users.

Novel wearable and contactless heart rate, respiratory rate, and oxygen saturation monitoring devices: a systematic review and meta‐analysis

“…Twelve studies of contactless devices provided respiratory rate range. Of these, seven studies of contactless devices contained respiratory rates <8 breaths.min ‐1 [13, 43, 46, 60, 62–64] and five recorded rates >30 breaths.min ‐1 [13, 43, 46, 60, 63]. Plots demonstrating the range of vital signs in wearable heart rate devices are in Fig.…”

“…Twenty‐eight wearable devices across 23 studies [13, 17–19, 21, 23, 25, 26, 28, 29, 31, 33, 36–38, 40–42, 48–50, 68, 69] and 10 contactless devices across nine studies [13, 42, 46, 51–53, 67, 70, 71] had enough data to assess the accuracy of heart rate compared with the reference standard with a Bland–Altman plot. There were 31 respiratory rate devices over 28 studies of wearable devices [13, 17, 18, 21–29, 31, 33, 35, 41, 54–60, 65, 66, 72, 73] and 13 devices over 13 studies of contactless devices [13, 43, 46, 53, 60, 62–64, 70, 71, 74–76] that utilised Bland–Altman plots.…”

“…S8). Limits of agreement ranged from 0.89 [71] to 9.21 [62], with four of the 12 [64, 70, 71, 74] devices having limits of agreements < 3 breaths.min ‐1 . The pooled estimate of mean of differences was 0.30 (−0.26–0.87) with pooled 95% limits of agreement −3.94– 4.29.…”

What is new in respiratory monitoring?

“…In 27 extubated intensive care patients, Chan et al[ 49 ] demonstrated that respiration rate monitoring based on infrared thermography agreed with gold standard chest movement counting by two observers (best R = 0.96) and outperformed respiration rate monitoring based on the often-used method of ECG-derived bioimpedance. Similarly, in a post-anesthesia recovery unit, Kwon et al[ 50 ] reported that respiration rate monitoring based on infrared thermography in 101 spontaneously breathing patients yielded an R 2 = 0.9 between infrared thermography and manual counting based on the clinical monitor. This extends earlier work by Hochhausen et al[ 51 ] who reported an accuracy (r = 0.607) of infrared thermography respiration rate monitoring compared to respiration rate derived from ECG-based bioimpedance in 28 postoperative patients.…”